我试图将MySQL数据库中的大型数据集(1300万行)读入pandas(0.17.1)。根据其中一条在线建议,我使用了chunksize
参数来执行此操作。
db = pymysql.connect(HOST, # localhost
port=PORT, # port
user=USER, # username
password=PASSW, # password
db=DATABASE) # name of the data base
df = pd.DataFrame()
query = "SELECT * FROM `table`;"
for chunks in pd.read_sql(query, con=db, chunksize=100000):
df = df.append(chunks)
但每次我运行此操作时都会收到TypeError: Argument 'rows' has incorrect type (expected list, got tuple)
错误。
当我没有使用chunksize参数并因此不生成生成器对象时,这是有效的。我可以看到mysql返回tuple-of-tuples
而不是list-of-tuples
。
所以,我的问题是为什么查询在正常情况下工作,我该怎么做才能确保我从数据库中获取一个元组列表以便我可以使用它?
完整的回溯看起来像这样
TypeError Traceback (most recent call last)
<ipython-input-20-efe94dcd2c70> in <module>()
8 df_horses = pd.DataFrame()
9 query = "SELECT * FROM `horses`;"
---> 10 for chunks in pd.read_sql(query, con=db, chunksize=10000):
11 df_horses = df_horses.append(chunks)
12 print df_horses.shape
/home/ubuntu/anaconda2/lib/python2.7/site-packages/pandas/io/sql.pyc in _query_iterator(cursor, chunksize, columns, index_col, coerce_float, parse_dates)
1563 yield _wrap_result(data, columns, index_col=index_col,
1564 coerce_float=coerce_float,
-> 1565 parse_dates=parse_dates)
1566
1567 def read_query(self, sql, index_col=None, coerce_float=True, params=None,
/home/ubuntu/anaconda2/lib/python2.7/site-packages/pandas/io/sql.pyc in _wrap_result(data, columns, index_col, coerce_float, parse_dates)
135
136 frame = DataFrame.from_records(data, columns=columns,
--> 137 coerce_float=coerce_float)
138
139 _parse_date_columns(frame, parse_dates)
/home/ubuntu/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc in from_records(cls, data, index, exclude, columns, coerce_float, nrows)
967 else:
968 arrays, arr_columns = _to_arrays(data, columns,
--> 969 coerce_float=coerce_float)
970
971 arr_columns = _ensure_index(arr_columns)
/home/ubuntu/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc in _to_arrays(data, columns, coerce_float, dtype)
5277 if isinstance(data[0], (list, tuple)):
5278 return _list_to_arrays(data, columns, coerce_float=coerce_float,
-> 5279 dtype=dtype)
5280 elif isinstance(data[0], collections.Mapping):
5281 return _list_of_dict_to_arrays(data, columns,
/home/ubuntu/anaconda2/lib/python2.7/site-packages/pandas/core/frame.pyc in _list_to_arrays(data, columns, coerce_float, dtype)
5355 def _list_to_arrays(data, columns, coerce_float=False, dtype=None):
5356 if len(data) > 0 and isinstance(data[0], tuple):
-> 5357 content = list(lib.to_object_array_tuples(data).T)
5358 else:
5359 # list of lists
TypeError: Argument 'rows' has incorrect type (expected list, got tuple)
答案 0 :(得分:0)
当使用chunksize时,我不知道“ pd.read_sql”后面不返回元组列表的原因。实际上,“ pd.read_sql”对于熊猫版本“ 0.23.4”不会引发任何错误。但是我也尝试使用熊猫版本“ 0.16.2”,但遇到的错误与您的错误相同。因此,在编写脚本之前,请务必检查您的熊猫版本。但是我确实知道一种解决熊猫“ 0.16.2”版本中错误的方法。
import pymysql as ps
import pandas as pd
db=ps.connect(user="user_name", passwd="password", host = 'host_name',
db='database_name')
cursor=db.cursor()
df=pd.DataFrame(columns=['column_name1','column_name2'])
query=""" select column_name1,column_name2 from table_name limit {0},{1}; """
limit=1000000
offset=0
try:
while True:
cursor.execute(query.format(offset,limit))
rows=pd.DataFrame(list(cursor.fetchall()),columns=
['column_name1','column_name2'])
df=pd.concat([df,rows],ignore_index=True)
offset=offset+limit
if len(rows['column_name1'])==0:
break
except:
pass